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Attention Score in Context
| Title |
How Electroencephalogram Reference Influences the Movement Readiness Potential?
|
|---|---|
| Published in |
Frontiers in Neuroscience, December 2017
|
| DOI | 10.3389/fnins.2017.00683 |
| Pubmed ID | |
| Authors |
Yuxia Hu, Lipeng Zhang, Mingming Chen, Xiaoyuan Li, Li Shi |
| Abstract |
Readiness potential (RP) based on electroencephalograms (EEG) has been studied extensively in recent years, but no studies have investigated the influence of the reference electrode on RP. In order to investigate the reference effect, 10 subjects were recruited and the original vertex reference (Cz) was used to record the raw EEG signal when the subjects performed a motor preparation task. The EEG was then transformed to the common average reference (CAR) and reference electrode standardization technique (REST) reference, and we analyzed the RP waveform and voltage topographies and calculated the classification accuracy of idle and RP EEG segments. Our results showed that the RP waveform and voltage topographies were greatly influenced by the reference, but the classification accuracy was less affected if proper channels were selected as features. Since the Cz channel is near the primary motor cortex, where the source of RP is located, using the REST and CAR references is recommended to get accurate RP waveforms and voltage topographies. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 36% |
| Student > Bachelor | 3 | 11% |
| Researcher | 3 | 11% |
| Student > Master | 3 | 11% |
| Professor | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 5 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 9 | 32% |
| Engineering | 7 | 25% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Physics and Astronomy | 2 | 7% |
| Computer Science | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 7 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 December 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#8,671
of 11,542 outputs
Outputs of similar age
#321,051
of 445,007 outputs
Outputs of similar age from Frontiers in Neuroscience
#152
of 186 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.